No returns even though Logs says there are HELP!!! #Frustrated

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Having trouble in backtester. The logs says I'm making profitable trades but the backtester says I'm not.

This happens with every algo so far...are my entries functions wrong? I'm using... order() and order_target()

Its a simple volume algo. If volume is > upper_limit then trade.

Any help much appreciated...(i'm beyond frustrated haha)

Thank you!!!!


from pytz import timezone  
import datetime  
import pytz  
import pandas as pd  
from quantopian.pipeline import Pipeline  
from quantopian.algorithm import attach_pipeline, pipeline_output  
import numpy as np

def initialize(context):  
    context.future =  continuous_future('CL', offset=0, roll='volume', adjustment='mul')  
    exchange_time = get_datetime('US/Eastern')  

    schedule_function(  
        myfunc,  
        date_rules.every_day(),  
        time_rules.market_open(minutes=5),  
        True  
      )

    schedule_function(  
        myfunc,  
        date_rules.every_day(),  
        time_rules.market_close(minutes=5),  
        True  
      )  
def myfunc(context,data):  
  pass  

##### ================================================================================================######

def handle_data(context, data):  
    exchange_time = pd.Timestamp(get_datetime()).tz_convert('US/Eastern')  
    cl_active = data.current(context.future, 'contract')  
    prices_custom_close = data.history(context.future, 'close', 30, '1m').resample('3T').last()   # 3min candles  
    current_price = data.current(cl_active,'price')  
    prices_custom_volume = data.history(context.future, 'volume', 30, '1m').resample('3T').last() # 3min candles  

    prices_custom_close = data.history(context.future, 'close', 20, '1m').resample('3T').last()  
    prices_custom_low = data.history(context.future, 'low', 20, '1m').resample('3T').last()  
    prices_custom_high = data.history(context.future, 'high', 20, '1m').resample('3T').last()  
    custom_volume = data.history(context.future, 'volume', 20, '1m').resample('3T').last()  
    upper_Long_lim = np.percentile(prices_custom_volume,80)  
    upper_Short_lim = np.percentile(prices_custom_volume,80)  
    previous_close  = float(prices_custom_close.iloc[-1])  
    current_close  = float(prices_custom_close.iloc[0])  
    previous_low = float(prices_custom_low.iloc[-1])  
    previous_high  = float(prices_custom_high.iloc[-1])  
    current_volume = float(prices_custom_close.iloc[0])  
    current_position = context.portfolio.positions[cl_active].amount  


### ======= LONG Entry & Exit  ========== ###  
    if  current_volume > upper_Long_lim and current_position==0:  
        order(cl_active, 1)  
        log.info('Long Entry')  
        log.info(current_price)  
    if current_price < previous_low and current_position > 0: # stop loss  
        order_target(cl_active, 0)  
        log.info('Long Stop')  
        log.info(current_price)

    elif current_price > (previous_high + .20) and current_position > 0: # profit target  
         log.info('Long PT')  

##### ============ SHORT Entry & Exit  ============== #####  
    if current_volume > upper_Short_lim and current_position == 0:  
        order(cl_active, -1)  
        log.info('Short Entry')  
        log.info(current_price)  

    if current_price > previous_high and current_position < 0: # stop loss  
        order_target(cl_active, 0)  
        log.info('Short Stop')  
        log.info(current_price)  
    elif current_price < (previous_close - .20) and current_position < 0:  
        order_target(cl_active,0)  
        log.info('Short PT')

The backtest engine determines the fill volume and price based upon the slippage model and also factors in commissions. One trick is to set the slippage and commissions to zero. This makes calculating the fill price much easier since it will simply be the last close price. Also, in the backtest results, there is a transactions list which shows exactly how orders are filled. Run a full backtest then click on the tab Activity->Transactions. This shows the individual trades which the backtester made. Step through each trade. You should be able see how your orders are filled and why they may differ from your expectations.

Perhaps start there. If there are specific trades which seem off, attach your backtest in a reply. It will be easier to troubleshoot that way.